Archive for the ‘Video’ Category

[Michael] posted some interesting uses of Nootropic’s latest shield, the Video Experimenter Shield, besed on a LM1881 video sync separator to detect the timing of the vertical and horizontal sync in a composite video signal. It’s one of the few examples of Arduino processing a live video signal, as previously seen with the Eye Shield (based on the same IC, but with no video out implemented). The image here is processed and sent out from the Arduino using a custom version of the TVoutLibrary. Wow.

The Video Experimenter shield can give your Arduino the gift of sight. In the Video Frame Capture project, I showed how to capture images from a composite video source and display them on a TV. We can take this concept further by processing the contents of the captured image to implement object tracking and edge detection.

The setup is the same as when capturing video frames: a video source like a camera is connected to the video input. The output select switch is set to “overlay”, and sync select jumper set to “video input”. Set the analog threshold potentiometer to the lowest setting.

If Kickstarter is nowadays best place to find new (or upcoming) toys to dream about, Gameduino is probably one of the most amazing pieces of hardware I’ve seen hosted there. The shield mounts its own FPGA able of 80ies style graphics and sounds for creating old-school, 8-bit video-games, pre-loaded with numerous sprites and set up for easy connection to a VGA display.

Gameduino is a game adapter for Arduino – or anything else with an SPI interface – built as a single shield that stacks up on top of the Arduino and has plugs for a VGA monitor and stereo speakers.

The sound and graphics are definitely old-school, but thanks to the latest FPGA technology, the sprite capabilities are a step above those in machines from the past.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .
cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

The first piece- data collection- is fairly standard. I use an electret microphone (which alone only produces a few mV output, far too low for our Arduino to use directly) with a transistor amplifier as the signal source, which is then sampled via the ADC on the Analog 0 pin of the Arduino.

To do spectrum analysis however, you need to capture signal over time, then process that data with what is known as a Fourier Transformation. This magical process takes a signal and breaks it down into buckets based upon frequencies found within the sample. This produces a remarkably good picture of the signal.. and if displayed, functions as a visual spectrum analyzer if looped over and over.

This post contains a library which performs both the sampling and the Fast Fourier Transformation completely in C in 8 bits, amazing fast considering that fact, and uses a few tricks to be really stingy on memory, which is at a premium on Arduino- especially with the TVout data space eating up quite a bit. Since the Atmega 328 only has 2k of RAM, every byte counts. Matrix math done like this is nothing short of awesome. Best of all, it’s usable as a library. Cut and paste the .cpp and .h into a new folder named “FFT” in the Libraries directory. My Arduino project code is adapted from the original code from the forum-posted Arduino program.

Laboral Centro de Arte, Spain, has commissioned the creation of a documentary about Arduino. The filmmakers are almost done with it and today they released the trailer to it. A lot of the footage was shot during the Arduino Uno meeting in March 2010, that took place at ITP, New York University.

The documentary is CC licensed, which means you guys can use it in class, public display, etc. The official release including the 45m TV version (with English and Spanish subtitles), the full interviews to all of us, videos taken at Makerbot, Adafruit, NYC Resistor, etc will be soon announced at the film’s website: arduinothedocumentary.org. If you want to volunteer making the subtitles in your own language, feel free to contact the guys behind it.

The SMSlingshot is an autonom working device, equipped with an ultra-high frequency radio, hacked arduino board, laser and batteries. Text messages can be typed on a phone-sized wooden keypad which is integrated in the also wooden slingshot. After the message is finished, the user can aim on a media facade and send/shoot the message straight to the targeted point. It will then appear as a colored splash with the message written within. The text message will also be real-time twittered – just in case.

have a look at the video on the official page of the project. Very interesting use of the sling in a digital way.

This project by the Spanish artist Ricardo Iglesias, is the result of a one and a half years long research process where he developed a series of robots with the ability of not just filming people with their embedded cameras, but to intelligently follow them increasing the creepyness level of the whole thing. The robot’s controller was prototyped with an Arduino board and took a long time to make the final design because it needs three switching power sources to feed the different parts of the design from a single battery (as Miguel, Hangar’s engineer reported).

You can check SonarMática’s official description here, and the official project website here.

I programmed an ATMega chip with Arduino to create my first 8-bit video synthesizer. The video signals are generated the same way as the audio files so what you see is what you hear.

I used the shell of an old CRT computer monitor as a case. It is flipped upside down and attached to some used office chair wheels.

The synthesizer is controlled by arcade game buttons and a pacman joystick.This synthesizer generates sine waves at various frequencies and amplitudes. I imagine doing more of these video synthesizers to create different patterns.